Agent skill

Detecting Cloud Threats With Guardduty

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge…

Apache-2.0Auto-check passedDevOps & Cloud

Install Detecting Cloud Threats With Guardduty

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-cloud-threats-with-guardduty -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-cloud-threats-with-guardduty --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/detecting-cloud-threats-with-guardduty .claude/skills/detecting-cloud-threats-with-guardduty && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
detecting-cloud-threats-with-guardduty
GitHub stars
34k
Token cost
~3.1k tokens
SKILL.md length
763 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge…

  • Works in 6 steps: Enable GuardDuty and Protection Plans → Configure Multi-Account Aggregation → Interpret Finding Types and Severity… → …
  • Establishing threat detection for AWS accounts
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls aws

What it does

Detecting Cloud Threats With Guardduty is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge and Lambda. Use when establishing threat detection for AWS accounts, investigating findings on compromised instances or credential abuse, or building automated incident-response playbooks.

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in DevOps & Cloud, covering File uploads and storage and Incident response. It works with Amazon Web Services. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Establishing threat detection for AWS accounts
  • Investigating findings on compromised instances
  • Credential abuse
  • Building automated incident-response playbooks

Example prompts

  • “/detecting-cloud-threats-with-guardduty”

Requirements

  • Python 3
  • Docker

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Enable GuardDuty and Protection Plans
  2. Configure Multi-Account Aggregation
  3. Interpret Finding Types and Severity Levels
  4. Build Automated Response with EventBridge
  5. Investigate Extended Threat Detection Attack Sequences
  6. Integrate with Security Hub and SIEM

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • aws

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use aws, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Detecting Cloud Threats With Guardduty loads about 3.1k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 107 tokens; SKILL.md has 763 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~107
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 763 words, ~3,067 tokens.

Download SKILL.mdSave it as .claude/skills/detecting-cloud-threats-with-guardduty/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
detecting-cloud-threats-with-guardduty
description
Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge and Lambda. Use when establishing threat detection for AWS accounts, investigating findings on compromised instances or credential abuse, or building automated incident-response playbooks.
domain
cybersecurity
subdomain
cloud-security
tags
amazon-guardduty, threat-detection, aws-security, runtime-monitoring, cloud-soc
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
PR.IR-01, ID.AM-08, GV.SC-06, DE.CM-01
mitre_attack
T1078.004, T1530, T1537, T1580, T1071

Detecting Cloud Threats with GuardDuty

When to Use

  • When establishing continuous threat detection for new or existing AWS accounts
  • When investigating GuardDuty findings related to compromised instances, credential abuse, or data exfiltration
  • When building automated incident response playbooks triggered by GuardDuty findings
  • When extending threat coverage to container workloads running on EKS, ECS, or Fargate
  • When enabling malware scanning for EBS volumes attached to suspicious EC2 instances

Do not use for Azure or GCP threat detection (see securing-azure-with-microsoft-defender or auditing-gcp-security-posture), for static code analysis, or for compliance posture monitoring (see implementing-aws-security-hub).

Prerequisites

  • AWS account with GuardDuty administrative permissions (guardduty:*)
  • AWS CloudTrail, VPC Flow Logs, and DNS query logs enabled (GuardDuty consumes these automatically)
  • AWS Organizations configured if deploying GuardDuty across a multi-account estate
  • EventBridge and Lambda configured for automated response workflows

Workflow

Step 1: Enable GuardDuty and Protection Plans

Activate GuardDuty at the organization level using a delegated administrator account. Enable all protection plans including S3 Protection, EKS Audit Log Monitoring, Runtime Monitoring, Malware Protection, RDS Login Activity, and Lambda Network Activity Monitoring.

bash
# Enable GuardDuty as organization delegated administrator
aws guardduty create-detector \
  --enable \
  --finding-publishing-frequency FIFTEEN_MINUTES \
  --data-sources '{
    "S3Logs": {"Enable": true},
    "Kubernetes": {"AuditLogs": {"Enable": true}},
    "MalwareProtection": {"ScanEc2InstanceWithFindings": {"EbsVolumes": true}}
  }'

# Enable Runtime Monitoring for EC2 and ECS
aws guardduty update-detector \
  --detector-id <detector-id> \
  --features '[
    {"Name": "RUNTIME_MONITORING", "Status": "ENABLED",
     "AdditionalConfiguration": [
       {"Name": "ECS_FARGATE_AGENT_MANAGEMENT", "Status": "ENABLED"},
       {"Name": "EC2_AGENT_MANAGEMENT", "Status": "ENABLED"}
     ]}
  ]'

# Designate delegated admin for multi-account
aws guardduty enable-organization-admin-account \
  --admin-account-id 111122223333
Step 2: Configure Multi-Account Aggregation

Automatically enroll all organization member accounts and configure finding export to a centralized S3 bucket for retention and SIEM ingestion.

bash
# Auto-enable GuardDuty for all org members
aws guardduty update-organization-configuration \
  --detector-id <detector-id> \
  --auto-enable-organization-members ALL \
  --features '[
    {"Name": "S3_DATA_EVENTS", "AutoEnable": "ALL"},
    {"Name": "EKS_AUDIT_LOGS", "AutoEnable": "ALL"},
    {"Name": "RUNTIME_MONITORING", "AutoEnable": "ALL"}
  ]'

# Configure finding export to S3
aws guardduty create-publishing-destination \
  --detector-id <detector-id> \
  --destination-type S3 \
  --destination-properties '{
    "DestinationArn": "arn:aws:s3:::guardduty-findings-centralized",
    "KmsKeyArn": "arn:aws:kms:us-east-1:123456789012:key/key-id"
  }'
Step 3: Interpret Finding Types and Severity Levels

GuardDuty classifies findings into four severity levels: Critical, High, Medium, and Low. Each finding type follows the format ThreatPurpose:ResourceType/ThreatName. Extended Threat Detection generates attack sequence findings that correlate multiple events across time.

Key finding categories:

  • Recon: Port scanning, API enumeration (e.g., Recon:EC2/PortProbeUnprotectedPort)
  • UnauthorizedAccess: Credential abuse, console logins from unusual locations
  • CryptoCurrency: Mining activity detected on instances (e.g., CryptoCurrency:EC2/BitcoinTool.B)
  • Impact: Resource hijacking, data destruction attempts
  • AttackSequence: Multi-stage attacks correlating initial access through lateral movement to impact (Critical severity)
Step 4: Build Automated Response with EventBridge

Create EventBridge rules that route GuardDuty findings to Lambda functions for automated containment actions such as isolating compromised EC2 instances, revoking IAM credentials, or blocking malicious IP addresses.

bash
# EventBridge rule for high/critical GuardDuty findings
aws events put-rule \
  --name GuardDutyHighSeverity \
  --event-pattern '{
    "source": ["aws.guardduty"],
    "detail-type": ["GuardDuty Finding"],
    "detail": {
      "severity": [{"numeric": [">=", 7]}]
    }
  }'

# Target Lambda function for auto-remediation
aws events put-targets \
  --rule GuardDutyHighSeverity \
  --targets '[{
    "Id": "AutoRemediateTarget",
    "Arn": "arn:aws:lambda:us-east-1:123456789012:function/guardduty-auto-remediate"
  }]'

Auto-remediation Lambda example for isolating a compromised EC2 instance:

python
import boto3

def lambda_handler(event, context):
    finding = event['detail']
    finding_type = finding['type']
    severity = finding['severity']

    if finding_type.startswith('UnauthorizedAccess:EC2') and severity >= 7:
        instance_id = finding['resource']['instanceDetails']['instanceId']
        ec2 = boto3.client('ec2')

        # Create isolation security group (no inbound/outbound rules)
        vpc_id = finding['resource']['instanceDetails']['networkInterfaces'][0]['vpcId']
        isolation_sg = ec2.create_security_group(
            GroupName=f'isolation-{instance_id}',
            Description='GuardDuty auto-isolation',
            VpcId=vpc_id
        )

        # Replace all security groups with isolation group
        ec2.modify_instance_attribute(
            InstanceId=instance_id,
            Groups=[isolation_sg['GroupId']]
        )

        # Tag instance for investigation
        ec2.create_tags(
            Resources=[instance_id],
            Tags=[{'Key': 'SecurityStatus', 'Value': 'ISOLATED'},
                  {'Key': 'GuardDutyFinding', 'Value': finding_type}]
        )

        return {'status': 'isolated', 'instance': instance_id}
Step 5: Investigate Extended Threat Detection Attack Sequences

Review Critical-severity attack sequence findings that correlate multiple signals across EC2, ECS, and EKS. These findings represent multi-stage attacks such as initial access through compromised credentials followed by persistence, lateral movement, and crypto mining.

bash
# List critical attack sequence findings
aws guardduty list-findings \
  --detector-id <detector-id> \
  --finding-criteria '{
    "Criterion": {
      "severity": {"Gte": 9},
      "type": {"Eq": ["AttackSequence:EC2/CompromisedInstanceGroup",
                       "AttackSequence:ECS/CompromisedCluster",
                       "AttackSequence:EKS/CompromisedCluster"]}
    }
  }'

# Get full finding details with attack sequence timeline
aws guardduty get-findings \
  --detector-id <detector-id> \
  --finding-ids <finding-id>
Step 6: Integrate with Security Hub and SIEM

Forward GuardDuty findings to AWS Security Hub for centralized aggregation and to external SIEM platforms via S3 export or Amazon Security Lake for long-term retention and cross-source correlation.

bash
# Verify GuardDuty integration with Security Hub
aws securityhub get-enabled-standards

# Enable Amazon Security Lake with GuardDuty as a source
aws securitylake create-data-lake \
  --configurations '[{
    "region": "us-east-1",
    "lifecycleConfiguration": {
      "expiration": {"days": 365}
    }
  }]'
Show full SKILL.md (358 more words)Show less

Key Concepts

TermDefinition
Extended Threat DetectionGuardDuty capability that correlates multiple signals across time to detect multi-stage attacks, generating Critical-severity attack sequence findings
Runtime MonitoringProtection plan that deploys a security agent to EC2 instances, ECS tasks, and EKS pods to detect runtime threats at the OS level
Finding SeverityFour-tier classification (Low, Medium, High, Critical) where Critical indicates confirmed multi-stage attacks requiring immediate response
Malware ProtectionOn-demand and automatic EBS volume scanning triggered by suspicious EC2 behavior to detect malware without agent installation
Delegated AdministratorOrganization member account designated to manage GuardDuty across all accounts in an AWS Organization
Suppression RuleFilter that automatically archives findings matching specific criteria to reduce noise from known benign activity
Threat IntelligenceIP reputation lists and domain threat feeds used by GuardDuty to identify communication with known malicious infrastructure

Tools & Systems

  • Amazon GuardDuty: Core threat detection service analyzing CloudTrail, VPC Flow Logs, DNS logs, and runtime telemetry
  • Amazon EventBridge: Serverless event bus for routing GuardDuty findings to automated response targets
  • AWS Security Hub: Centralized security findings aggregation supporting automated remediation workflows
  • Amazon Security Lake: OCSF-normalized data lake for long-term security log retention and cross-service correlation
  • Amazon Detective: Graph-based investigation service that visualizes relationships between GuardDuty findings, resources, and API activity

Common Scenarios

Scenario: Cryptocurrency Mining Detected on ECS Cluster

Context: GuardDuty generates a CryptoCurrency:Runtime/BitcoinTool.B finding with High severity targeting an ECS Fargate task. Runtime Monitoring detected the execution of a mining binary within a container.

Approach:

  1. Review the finding details to identify the ECS cluster, task definition, and container image
  2. Stop the affected ECS task immediately and quarantine the container image in ECR
  3. Check CloudTrail for the ecs:RegisterTaskDefinition and ecs:RunTask calls to identify who deployed the malicious image
  4. Scan the Docker image with ECR enhanced scanning to identify the embedded mining binary
  5. Review IAM credentials used to push the image and revoke compromised access
  6. Update ECR image scanning policies to block images with known mining signatures

Pitfalls: Stopping the task without preserving the container image loses forensic evidence. Failing to trace back to the RegisterTaskDefinition API call misses the initial compromise vector.

Output Format

GuardDuty Threat Detection Summary
====================================
Account: 123456789012 (production)
Region: us-east-1
Period: 2025-02-01 to 2025-02-23

CRITICAL FINDINGS (Immediate Action Required):
[CRIT-001] AttackSequence:EC2/CompromisedInstanceGroup
  - Instances: i-0abc123def, i-0def456abc
  - Attack Chain: Credential theft -> Persistence -> Crypto mining
  - First Signal: 2025-02-15T08:23:00Z
  - Duration: 4 hours across 3 stages
  - Status: Auto-isolated via Lambda

HIGH FINDINGS:
[HIGH-001] UnauthorizedAccess:IAMUser/MaliciousIPCaller
  - Principal: arn:aws:iam::123456789012:user/ci-deploy
  - Source IP: 198.51.100.42 (Tor exit node)
  - API Calls: 47 calls to ec2:RunInstances
  - Status: Access key deactivated

[HIGH-002] CryptoCurrency:Runtime/BitcoinTool.B
  - Resource: ECS Task arn:aws:ecs:us-east-1:123456789012:task/cluster/task-id
  - Image: 123456789012.dkr.ecr.us-east-1.amazonaws.com/app:v2.1
  - Process: /tmp/.hidden/xmrig --pool stratum+tcp://pool.example.com:3333
  - Status: Task stopped, image quarantined

STATISTICS:
  Total Findings: 23
  Critical: 1 | High: 3 | Medium: 8 | Low: 11
  Auto-Remediated: 4
  Pending Investigation: 2

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/detecting-cloud-threats-with-guardduty of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Questions about Detecting Cloud Threats With Guardduty

What does Detecting Cloud Threats With Guardduty do?

Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge…. Detecting Cloud Threats With Guardduty is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge and Lambda.

When should I use Detecting Cloud Threats With Guardduty?

Detecting Cloud Threats With Guardduty fits situations like: establishing threat detection for AWS accounts; investigating findings on compromised instances; credential abuse; building automated incident-response playbooks.

How do I install Detecting Cloud Threats With Guardduty in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-cloud-threats-with-guardduty -a claude-code`. Or copy the skill folder (skills/detecting-cloud-threats-with-guardduty in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/detecting-cloud-threats-with-guardduty in your project. Claude Code loads it when a task matches its description.

How do I install Detecting Cloud Threats With Guardduty in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-cloud-threats-with-guardduty -a codex`. Or copy the skill folder (skills/detecting-cloud-threats-with-guardduty in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/detecting-cloud-threats-with-guardduty in your project. Codex loads it when a task matches its description.

Can I use Detecting Cloud Threats With Guardduty in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-cloud-threats-with-guardduty -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/detecting-cloud-threats-with-guardduty, .gemini/skills/detecting-cloud-threats-with-guardduty, .github/skills/detecting-cloud-threats-with-guardduty and .opencode/skills/detecting-cloud-threats-with-guardduty in your project.

What does Detecting Cloud Threats With Guardduty need to run?

Going by SKILL.md and its folder, Detecting Cloud Threats With Guardduty needs Python for the scripts in its folder and the command-line tools its instructions call (aws). Our summary lists: Python 3; Docker.

Does Detecting Cloud Threats With Guardduty access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Detecting Cloud Threats With Guardduty safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Detecting Cloud Threats With Guardduty use?

Detecting Cloud Threats With Guardduty is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Detecting Cloud Threats With Guardduty use?

About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 575 tokens, read only when the agent opens those files.

What are the alternatives to Detecting Cloud Threats With Guardduty?

Skills that share tags, products or a category with Detecting Cloud Threats With Guardduty: Storage S3 Resiliency Expertise (aws/tools-for-devops-agent, 103 stars), AWS Essentials (ericrisco/rsc-harness, 180 stars), AWS Advisor (diegosouzapw/awesome-omni-skills, 159 stars) and AWS Incident Response (TracecatHQ/tracecat, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Detecting Cloud Threats With Guardduty?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.